Effect of common antinutritive factors and fibrous feedstuffs in pig diets on amino acid digestibilities with special emphasis on threonine1,2
Bibliographic record
Abstract
Most feedstuffs contain antinutritive factors (ANF) such as insoluble fibers, lignins, tannins, and lectins. Intake of these ANF has the ability to reduce nutrient digestibility and to increase endogenous protein losses, such as through increased intestinal mucus secretion. The objective of this experiment was to determine the apparent ileal digestibilities (AID) of AA of 6 ANF-enriched diets to estimate endogenous protein loss associated with these ingredients in diets for young pigs. Forty-two 10-kg BW pigs fitted with a simple T-cannula at the distal ileum were randomly assigned to 1 of 7 casein-based diets with: no supplement (control), 100 g/kg of canola meal (CM), 100 g/kg of wheat bran (WB), 150 g/kg of barley (BR), 22.5 g/kg of lignin (LG), 15 g/kg of kidney beans [as a lectin (LE) source], and 15 g/kg of tannins (TN). All diets were formulated to be similar in N, indispensable AA, and caloric contents. After a 7-d adaptation to the test diets, N balance was conducted for 5 d, followed by 24 h of collection of digesta for analyses of AA. Pigs fed BR had 17% lower ADG and 15% lower feed conversion ratio (P < 0.05) compared with control and CM pigs. Pigs fed diets containing WB and BR had lower N retention as a percentage of absorbed N compared with all other groups (P = 0.03). The AID for CP was lower in BR, WB, and LE pigs compared with control. Of the AA, AID of Thr was notably lowest in BR, WB, and TN pigs (P < 0.05). The standardized ileal digestibility was lower in WB and BR pigs for most indispensable AA. Altogether, these data suggest that hemicellulose fiber, at concentrations typical in commercial swine diets, reduces AID of AA by increasing endogenous losses. Understanding the differential effects of ANF on endogenous losses of individual dietary AA will improve the accuracy of diet formulation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".